AI governance needs authority and evidence, not just model controls
ENTITY treats AI applications and agents as actors operating under explicit delegated authority. It keeps model output, provenance, rights, evidence and real-world claims separate so access to infrastructure does not become sovereign authority.
Authority before agency
An AI process can call tools, write files or query databases without becoming the sovereign controller of those resources. ENTITY requires scoped, revocable authority for protected actions and preserves the identity that granted that authority.
Data and model lineage
Governed lineage can connect source datasets, usage rights, transformations, model artifacts, signed events, generated outputs and downstream economic consequences. BTDU provides governed information topology while ENTITY remains the authority, rights, provenance and economic layer.
Signed output is not truth
A signature proves that a key signed a payload. It does not prove the model output is factually correct. ENTITY keeps cryptographic verification, protocol validity and external-world evidence as separate verification boundaries.
Training and derivation rights
Possession of data does not automatically grant permission to train, derive, redistribute or commercialize. ENTITY can express those permissions and restrictions explicitly, along with any separately agreed economic participation terms.
Standards mapping without false certification
The AI domain package can map deployment facts to frameworks such as the NIST AI RMF. A mapping is evidence and configuration support; it is not an automatic certification or legal conclusion.
Independent scrutiny
ENTITY v3.4.2 exposes an external verification challenge, hardware-backed custody qualification, physical multi-host qualification, certified-device pilot, independent security-audit RFP and independent assessor review. Reproducible failures and negative findings are useful evidence.